Outdoor Universal Thermal Comfort Index Climatology for Alaska — Oak Academic Publishing
Research ArticleOpen AccessGoogle Scholar indexed
Outdoor Universal Thermal Comfort Index Climatology for Alaska
Geophysical Institute, Department of Atmospheric Sciences, College of Natural Science and Mathematics, University of Alaska Fairbanks, Fairbanks, USA
1 Geophysical Institute, Department of Atmospheric Sciences, College of Natural Science and Mathematics, University of Alaska Fairbanks, Fairbanks, USA
Data from 456 surface meteorological sites in Alaska, eastern Russia and northwest Canada for 1979-2017 were used to model hourly universal thermal comfort indices (UTCIs) under consideration of Alaska-appropriate clothing. The results served to determine a high-resolution climatology of thermal comfort levels for Alaska at various temporal and spatial scales as well as the frequency of thermal stress levels. On 1979-2017 average, various degrees of cold stress occurred with highest percentage on the Alaska West Coast and along the Arctic Ocean. In the continental and Inside Passage region, no thermal stress had the highest percentage of occurrence. In Interior Alaska, both strong heat and extreme cold stress occurred occasionally. At most sites and in all Alaska K ö ppen-Geiger bio-climate regions, the absolute range between monthly means of daily minimum and maximum UTCIs was larger than that of monthly means of daily minimum and maximum air temperatures. Major contributors to thermal discomfort (shortwave radiation, air temperature, moisture, wind speed) varied among bio-climate regions and in the diurnal and annual courses.
Keywordsversal Thermal ComUTCIUnifort IndexThermal Stress in AlaskaBio-Climate of AlaskaThermal Stress Climatology of Alaska
US Census Bureau (2019) 2018 National Population Projections.
Arctic-Council (2009) Arctic Marine Shipping Assessment 2009 Report. 194 p.
Mölders, N. and Gende, S. (2016) On the Limits to Manage Air-Quality in Glacier Bay. Journal of Environmental Protection, 7, 1923-1955. https://doi.org/10.4236/jep.2016.712151
Laschewski, G. and Jendritzky, G. (2002) Effects of the Thermal Environment on Human Health: An Investigation of 30 Years of Daily Mortality Data from SW Germany. Climate Research, 21, 91-103. https://doi.org/10.3354/cr021091
Kysely, J., Pokorna, L., Kyncl, J. and Kriz, B. (2009) Excess Cardiovascular Mortality Associated with Cold Spells in the Czech Republic. BMC Public Health, 9, 19. https://doi.org/10.1186/1471-2458-9-19
Ma, W., Yang, C., Chu, C., Li, T., Tan, J. and Kan, H. (2013) The Impact of the 2008 Cold Spell on Mortality in Shanghai, China. International Journal of Biometeorology, 57, 179-184. https://doi.org/10.1007/s00484-012-0545-7
Di Napoli, C., Pappenberger, F. and Cloke, H.L. (2018) Assessing Heat-Related Health Risk in Europe via the Universal Thermal Climate Index (UTCI). International Journal of Biometeorology, 62, 1155-1165. https://doi.org/10.1007/s00484-018-1518-2
Skutecki, R., Jalali, R., Dragańska, E., Cymes, I., Romaszko, J. and Glińska-Lewczuk, K. (2019) UTCI as a Bio-Meteorological Tool in the Assessment of Cold-Induced Stress as a Risk Factor for Hypertension. Science of the Total Environment, 688, 970-975. https://doi.org/10.1016/j.scitotenv.2019.06.280
Blazejczyk, K., Epstein, Y., Jendritzky, G., Staiger, H. and Tinz, B. (2012) Comparison of UTCI to Selected Thermal Indices. International Journal of Biometeorology, 56, 515-535. https://doi.org/10.1007/s00484-011-0453-2
Krüger, E.L., Minella, F.O. and Matzarakis, A. (2014) Comparison of Different Methods of Estimating the Mean Radiant Temperature in Outdoor Thermal Comfort Studies. International Journal of Biometeorology, 58, 1727-1737. https://doi.org/10.1007/s00484-013-0777-1
Buzan, J.R., Oleson, K. and Huber, M. (2015) Implementation and Comparison of a Suite of Heat Stress Metrics within the Community Land Model Version 4.5. Geoscientific Model Development, 8, 151-170. https://doi.org/10.5194/gmd-8-151-2015
Zare, S., Hasheminejad, N., Shirvan, H.E., Hemmatjo, R., Sarebanzadeh, K. and Ahmadi, S. (2018) Comparing Universal Thermal Climate Index (UTCI) with Selected Thermal Indices/Environmental Parameters During 12 Months of the Year. Weather and Climate Extremes, 19, 49-57. https://doi.org/10.1016/j.wace.2018.01.004
Houghton, F.C. and Yaglou, C.P. (1923) Determining Equal Comfort Lines. J. Am. Soc. Heating and Ventilation in England, 29, 165-176.
Fountain, M. and Huizenga, C. (1995) A Thermal Sensation Model for Use by the Engineering Profession-Results of Cooperative Research between the American Society of Heating, Refrigeration, and Air-Conditioning Engineers, Inc. and Environmental Analytics. 1-55.
Salata, F., Golasi, I., De Lieto Vollaro, R. and De Lieto Vollaro, A. (2016) Outdoor Thermal Comfort in the Mediterranean Area. A Transversal Study in Rome, Italy. Building and Environment, 96, 46-61. https://doi.org/10.1016/j.buildenv.2015.11.023
Jendritzky, G. and Nubler, W. (1981) A Model Analyzing the Urban Thermal Environment in Physiologically Significant Terms. Archives of Meteorology and Geophysical Bioclimatology, 29, 313-326. https://doi.org/10.1007/BF02263308
Pickup, J. and De Dear, R. (2000) An Outdoor Thermal Comfort Index (OUT-SET*)-Part I—The Model and Its Assumptions. 5th International Congress of Biometeorology and International Conference on Urban Climatology, Macquarie University, Sydney, 279-283.
ASHRAE (2001) ASHRAE Fundamentals Handbook 2001. SI Edition. 892 p.
Thorsson, S., Lindqvist, M. and Lindqvist, S. (2004) Thermal Bioclimatic Conditions and Patterns of Behaviour in an Urban Park in Göteborg, Sweden. International Journal of Biometeorology, 48, 149-156. https://doi.org/10.1007/s00484-003-0189-8
Golasi, I., Salata, F., De Lieto Vollaro, E. and Coppi, M. (2018) Complying with the Demand of Standardization in Outdoor Thermal Comfort: A First Approach to the Global Outdoor Comfort Index (GOCI). Building and Environment, 130, 104-119. https://doi.org/10.1016/j.buildenv.2017.12.021
Lindberg, F., Holmer, B., Thorsson, S. and Rayner, D. (2013) Characteristics of the Mean Radiant Temperature in High Latitude Cities-Implications for Sensitive Climate Planning Applications. International Journal of Biometeorology, 58, 613-627. https://doi.org/10.1007/s00484-013-0638-y
Gommershtadt, O., Konstantinov, P., Varentsov, M. and Baklanov, A. (2020) Modeling Technology for Assessment of Summer Thermal Comfort Conditions of Arctic City on Microscale: Application for City of Apatity. In: Vasenev, V., Dovletyarova, E., Cheng, Z., Valentini, R. and Calfapietra, C., Eds., Green Technologies and Infrastructure to Enhance Urban Ecosystem Services. SSC 2018, Springer Geography, Springer, Cham, 66-75. https://doi.org/10.1007/978-3-030-16091-3_10
Kottek, M., Grieser, J., Beck, C., Rudolf, B. and Rubel, F. (2006) World Map of the Köppen-Geiger Climate Classification Updated. Meteorologische Zeitschrift, 15, 259-263. https://doi.org/10.1127/0941-2948/2006/0130
Harris, I., Jones, P.D., Osborn, T.J. and Lister, D.H. (2013) Updated High-Resolution Grids of Monthly Climatic Observations—The CRU TS3.10 Dataset. International Journal of Climatology, 34, 623-642. https://doi.org/10.1002/joc.3711
Schneider, U., Fuchs, T., Meyer-Christoffer, A. and Rudolf, B. (2008) Global Precipitation Analysis Products of the GPCC. Global Precipitation Climatology Centre (GPCC), Deutscher Wetterdienst, Offenbach, Germany, 12 p.
Mölders, N. and Kramm, G. (2018) Climatology of Air Quality in Arctic Cities-Inventory and Assessment. Open Journal of Air Pollution, 7, 48-93. https://doi.org/10.4236/ojap.2018.71004
Geiger, R. (1961) überarbeitete Neuausgabe Von Geiger, R. Köppen Geiger/Klima der Erde. (Wandkarte 1:16 Mill.).
Shulski, M. and Wendler, G. (2007) The Climate of Alaska. 216 p.
Bieniek, P.A., Walsh, J.E., Thoman, R.L. and Bhatt, U.S. (2014) Using Climate Divisions to Analyze Variations and Trends in Alaska Temperature and Precipitation. Journal of Climate, 27, 2800-2818. https://doi.org/10.1175/JCLI-D-13-00342.1
Pappenberger, F., Jendritzky, G., Staiger, H., Dutra, E., Di Giuseppe, F., Richardson, D.S. and Cloke, H.L. (2015) Global Forecasting of Thermal Health Hazards: The Skill of Probabilistic Predictions of the Universal Thermal Climate Index (UTCI). International Journal of Biometeorology, 59, 311-323. https://doi.org/10.1007/s00484-014-0843-3
Jendritzky, G., Bröde, P., Fiala, D., Habvenith, G., Weihs, P., Batchvarova, E. and Dedear, R. (2009) Der Thermische Klimaindex UTCI. 96-101.
Bröde, P., Fiala, D., Błażejczyk, K., Holmér, I., Jendritzky, G., Kampmann, B., Tinz, B. and Havenith, G. (2012) Deriving the Operational Procedure for the Universal Thermal Climate Index (UTCI). International Journal of Biometeorology, 56, 481-494. https://doi.org/10.1007/s00484-011-0454-1
Psikuta, A., Fiala, D., Laschewski, G., Jendritzky, G., Richards, M., Błażejczyk, K., Mekjavič, I., Rintamäki, H., De Dear, R. and Havenith, G. (2012) Validation of the Fiala Multi-Node Thermophysiological Model for UTCI Application. International Journal of Biometeorology, 56, 443-460. https://doi.org/10.1007/s00484-011-0450-5
Fiala, D., Havenith, G., Bröde, P., Kampmann, B. and Jendritzky, G. (2012) UTCI-Fiala Multi-Node Model of Human Heat Transfer and Temperature Regulation. International Journal of Biometeorology, 56, 429-441. https://doi.org/10.1007/s00484-011-0424-7
Havenith, G., Fiala, D., Błazejczyk, K., Richards, M., Bröde, P., Holmér, I., Rintamaki, H., Benshabat, Y. and Jendritzky, G. (2012) The UTCI-Clothing Model. International Journal of Biometeorology, 56, 461-470. https://doi.org/10.1007/s00484-011-0451-4
Mölders, N. and Kramm, G. (2014) Lectures in Meteorology. Springer Nature, Switzerland, 591 p. https://doi.org/10.1007/978-3-319-02144-7
Baldasano, J.M., Valera, E. and Jiménez, P. (2003) Air Quality Data from Large Cities. The Science of the Total Environment, 307, 141-165. https://doi.org/10.1016/S0048-9697(02)00537-5
Sundqvist, H., Berge, E. and Kristjánsson, J.E. (1989) Condensation and Cloud Parameterization Studies with a Mesoscale Numerical Weather Prediction Model. Monthly Weather Review, 117, 1641-1657. https://doi.org/10.1175/1520-0493(1989)117 2.0.CO;2
Sormunen, E. (2009) Repetitive Work in the Cold-Work Ability, Musculoskeletal Symptoms and Thermal and Neuromuscular Responses in Food Industry Workers. University of Oulu, Oulu.
Pantavou, K.G., Lykoudis, S.P. and Nikolopoulos, G.K. (2016) Milder Form of Heat-Related Symptoms and Thermal Sensation: A Study in a Mediterranean Climate. International Journal of Biometeorology, 60, 917-929. https://doi.org/10.1007/s00484-015-1085-8
Oke, T.R. (1995) Boundary Layer Climates. Routledge, 464 p.
Huang, J., Cedeño-Laurent, J.G. and Spengler, J.D. (2014) Citycomfort+: A Simulation-Based Method for Predicting Mean Radiant Temperature in Dense Urban Areas. Building and Environment, 80, 84-95. https://doi.org/10.1016/j.buildenv.2014.05.019
Dimiceli, V.E., Piltz, S.F. and Amburn, S.A. (2013) Black Globe Temperature Estimate for the WBTG Index. In: Kim, H., Ao, S.I. and Rieger, B., Eds., IAENG Transactions on Engineering Technologies. Lecture Notes in Electrical Engineering, Springer, Dordrecht, 323-334. https://doi.org/10.1007/978-94-007-4786-9_26
Köppen, W. (1900) Versuch Einer Klassifikation der Klimate, Vorzugsweise Nach Ihren Beziehungen Zur Pflanzenwelt. Geographische Zeitschrift, 6, 657-679.
Von Storch, H. and Zwiers, F.W. (1999) Statistical Analysis in Climate Research. Cambridge University Press, Cambridge, 484 p. https://doi.org/10.1017/CBO9780511612336
Gong, S.L., Zhao, T.L., Sharma, S., Toom-Sauntry, D., Lavoué, D., Zhang, X.B., Leaitch, W.R. and Barrie, L.A. (2010) Identification of Trends and Interannual Variability of Sulfate and Black Carbon in the Canadian High Arctic: 1981-2007. Journal of Geophysical Research: Atmospheres, 115. https://doi.org/10.1029/2009JD012943
Kim, J., Waliser, D.E., Mattmann, C.A., Mearns, L.O., Goodale, C.E., Hart, A.F., Crichton, D.J., Mcginnis, S., Lee, H., Loikith, P.C. and Boustani, M. (2013) Evaluation of the Surface Climatology over the Conterminous United States in the North American Regional Climate Change Assessment Program Hindcast Experiment Using a Regional Climate Model Evaluation System. Journal of Climate, 26, 5698-5715. https://doi.org/10.1175/JCLI-D-12-00452.1
Mölders, N. (2011) Land-Use and Land-Cover Changes: Impact on Climate and Air Quality. Springer Nature, Switzerland, 193 p. https://doi.org/10.1007/978-94-007-1527-1
Winther, M., Christensen, J.H., Plejdrup, M.S., Ravn, E.S., Eriksson, ó.F. and Kristensen, H.O. (2014) Emission Inventories for Ships in the Arctic Based on Satellite Sampled AIS Data. Atmospheric Environment, 91, 1-14. https://doi.org/10.1016/j.atmosenv.2014.03.006
Lam, C.K.C. and Lau, K.K. (2018) Effect of Long-Term Acclimatization on Summer Thermal Comfort in Outdoor Spaces: A Comparative Study between Melbourne and Hong Kong. International Journal of Biometeorology, 62, 1311-1324. https://doi.org/10.1007/s00484-018-1535-1
Matzarakis, A., Fröhlich, D., Bermon, S. and Adami, P. (2018) Quantifying Thermal Stress for Sport Events—The Case of the Olympic Games 2020 in Tokyo. Atmosphere, 9, 479. https://doi.org/10.3390/atmos9120479
Founda, D., Pierros, F., Katavoutas, G. and Keramitsoglou, I. (2019) Observed Trends in Thermal Stress at European Cities with Different Background Climates. Atmosphere, 10, 436. https://doi.org/10.3390/atmos10080436